important cause of blindness in the world. We are presenting here an application of the Symbolic Data Analysis approach to an … intervene. The Symbolic Data Analysis approach aims at studying classes of individuals considered as new units. These units are …, the results obtained are compared to those previously provided by multiple logistic regression analysis. Symbolic Data …

dissimilarities is given. This type of data fall in the wider class of symbolic data (see Bock and Diday (2000)). We model three …

dissimilarities is given. This type of data fall in the wider class of symbolic data (see Bock and Diday (2000)). We model three … of data fall in the wider class of symbolic data (see Bock and Diday (2000)). We model three-way two-mode data consisting … distribution of values (a histogram). In these cases, the data matrix consists of symbolic data. By now, MDS of symbolic data can …

fuzzy data fall in the wider class of symbolic data (Bock and Diday, 2000). Denoeux and Masson (2000) have proposed to model …

fuzzy data fall in the wider class of symbolic data (Bock and Diday, 2000). Denoeux and Masson (2000) have proposed to model … is unknown, but the range of the dissimilarity is given. Such fuzzy data fall in the wider class of symbolic data (Bock … discuss the use of SymScal on empirical dissimilarity intervals of sounds. Keywords: Multidimensional scaling, Symbolic data …

Histogram time series (HTS) and interval time series (ITS) are examples of symbolic data sets. Though there have been …

interval data obtained by symbolic data analysis (SDA). SDA is a new data analysis technique which captures the value of a … first. We then proposed the standardization method of interval symbolic data and conducted a simulation study to evaluate …